Health-related physical fitness (HRPF) has demonstrated high clinical relevance, and its level is associated with the ability to perform activities of daily living with vigor and a lower risk of chronic disease. Consequently, exercise prescription guidelines recommend improving HRPF as a focus for prevention and rehabilitation programs. Measuring and tracking HRPF often requires specialized equipment and personnel, which are expensive and less applicable to the general population. Wearables may mitigate this issue by providing useful estimates of the HRPF.

Health-related physical fitness (HRPF) has high clinical relevance [1]. It is associated with the ability to perform activities of daily living with vigor and a lower risk of chronic disease [2]. Consequently, exercise prescription guidelines recommend improving HRPF as a focus for prevention and rehabilitation programs [3]. The American College of Sports Medicine (ACSM) [3] grouped the HRFP into five domains: cardiorespiratory endurance, body composition, muscular strength, muscular endurance, and flexibility. However, measuring and tracking the fitness levels for all HRPF domains requires specialized laboratory equipment and personnel, which are expensive and less applicable to the general population. Wearable technology mitigates this issue and has proven to be a reliable alternative capable of providing useful estimates of the HRPF [4] [5] [6, 7]. Previous work has predicted ACSM HRPF domains from anthropometric and laboratory bioelectrical impedance analysis data (BIA) [8] [9]. Nevertheless, their data are based on the National Fitness Award (NFA), a nationwide test used to assess the physical fitness of the general South Korean population that is collected using specialized laboratory equipment under the supervision of health professionals.

Current advances in wearables may allow us to estimate the fitness level for all HRPF domains using only smartwatch data, enabling economic, non-intrusive predictions and being available during the user's daily routine. The complete characterization of health-related fitness as a multidimensional depiction of the user's fitness status can be used to track health status continuously and to design specialized training prescriptions. The main goal of this study is to estimate the fitness level for all HRFP domains from data obtained from smartwatches during unsupervised activities of daily living. We hypothesized that data from smartwatches could be used to estimate the fitness levels from all HRPF domains.

Inclusion Criteria:

Group 1 (Aerobically Trained)

• 20-60 years old
• actively training or competing over the past 2 years
• 3 or more days of vigorous activity accumulating approximately least 1500 MET min/week or 7 days of any combination of walking, moderate, or vigorous intense activities achieving a minimum of 3000 MET min/week

Group 2 (Strength trained)

• 20-60 years old
• actively training or competing over the past 2 years
• 3 or more days of muscle-strengthening exercise at an intensity of approximately 5 out of 10

Group 3 (Not actively training)

• 20-60 years old
• actively training or competing over the past 2 years
• 3 or more days of muscle-strengthening exercise at an intensity of approximately 5 out of 10

Group 5 (High flexibility)

• 20-60 years old
• Sit-and-reach performance is categorized as "very good" or excellent based on the American College of Sports Medicine's sit-and-reach evaluation criteria (Table 4.16 of ACSM's Guidelines for Exercise Testing and Prescription 9th edition).

Exclusion Criteria:

Exclusion criteria are the same for all groups.

• History of cardiovascular disease (Cardiac, peripheral vascular, or cerebrovascular disease)
• History of stable or unstable angina
• History of cardiac dysrhythmias causing symptoms or hemodynamic consequences
• History of hypertrophic cardiomyopathy
• History of cardiac valvular disease (e.g., aortic stenosis)
• History of pulmonary disease (Chronic obstructive pulmonary disease, asthma, interstitial lung disease, or cystic fibrosis)
• History of pulmonary embolus
• History of suspected or known aneurysm
• History of metabolic disease (Diabetes mellitus (type I or II), thyroid disorders, renal or liver disease
• History of renal disease
• History of neuromotor, musculoskeletal, or rheumatoid disorders that are exacerbated by exercise
• Current acute systemic infection, accompanied by fever and body aches.
• Pain or discomfort in the chest, neck, jaw, arms, or other areas that may be due to myocardial ischemia (lack of adequate circulation)
• Shortness of breath at rest, during daily activities, or with mild exertion
• Dizziness or syncope (fainting)
• Orthopnea (breathing discomfort when not in an upright position) or paroxysmal nocturnal dyspnea (interrupted breathing at night)
• Ankle edema (swelling)
• Palpitations (abnormal rapid beating of the heart) or tachycardia (rapid heartbeat)
• Intermittent claudication (cramping pain and weakness in legs, especially calves, during walking due to inadequate blood supply to muscles)
• Known heart murmur (atypical heart sound indicating a structural or functional abnormality)
• Unusual or unexplained fatigue
• Severe arterial hypertension (i.e., systolic blood pressure of >200 mm Hg and/or a diastolic blood pressure of >110 mm Hg) at rest.

he study population consists of healthy adult individuals categorized into four distinct groups based on their physical activity habits and fitness characteristics. These groups include:

Aerobically Trained Individuals

Participants actively engaged in aerobic exercise training (e.g., running, cycling, swimming) for at least two years.

Likely to have higher cardiovascular fitness and endurance levels compared to other groups.

Strength-Trained Individuals

Participants actively engaged in regular weight training or resistance exercises.

Expected to exhibit higher levels of muscle strength and hypertrophy. Non-Training Individuals

Participants who are not engaged in regular aerobic or weight training exercises.

Represent a baseline or control group with typical sedentary or minimally active lifestyles.

Highly Flexible Individuals

Participants identified by achieving high scores on flexibility assessments, regardless of their training status.

Expected to have greater joint range of mot